Natural Resources, School of


Date of this Version



Originally published by the Department of Geography, University of California, Santa Barbara, online at


Copyright 2008, Qingfeng (Gene) Guan. Used by permission.


pRPL is an open-source1 general-purpose parallel Raster Processing programming Library developed by Qingfeng Guan, in the Department of Geography, University of California, Santa Barbara. pRPL encapsulates complex parallel computing utilities and routines specifically for raster processing (e.g., raster data decomposition, distribution and gathering among multiple processors, inter-processor communication and data exchange), and provides an easy-to-use interface for users to parallelize almost any raster processing algorithm with any arbitrary neighborhood (or moving window) configuration. pRPL enables the implementation of parallel raster-processing algorithms without requiring a deep understanding of parallel computing and programming, thus it greatly reduces the development complexity. Moreover, even though pRPL was developed for massive-volume geographical raster processing, it can also be used for other large-scale raster-like computations such as image processing and cellular automata (CA). In fact, pRPL was first developed primarily for a geographical CA model. That is why you will see many terminologies from CA in this document, e.g., cell, cellspace, neighborhood, and transition. An "Appendix" and a compressed file of the source code for pRPL are attached (below) as Related files.